
AI Data Quality and Standards Professional
22 hours ago
We are seeking a diligent and detail-focused data quality specialist to maintain annotation standards and drive continuous improvements to keep AI data accurate, efficient, and scalable.
Responsibilities:
- Perform quality audits on annotated datasets to ensure they meet established guidelines and quality benchmarks.
- Leverage metrics such as F1 score and inter-annotator agreement to evaluate data quality.
- Analyze annotation errors, trends, and project documentation to identify root causes and propose remediation strategies.
- Manage edge-case annotations to ensure quality and identify improvement areas.
- Use annotation and quality control tools to perform reviews and track quality metrics.
- Provide feedback for clarifications or improvements of project guidelines.
- Identify automation opportunities and contribute to documentation of quality standards and procedures.
Requirements:
- 1+ years of experience as a data analyst with exposure to data quality and/or data annotation, ideally in an AI/ML context.
- Familiarity with basic concepts of AI/ML pipelines and data.
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